On the Fault Line: A Qualitative Exploration of High School Teachers’ Involvement with Student Mental Health Issues

School-based mental health (SBMH) research often underplays the crucial role that teachers play in supporting student mental health, even as teachers often find themselves encountering student mental health issues. Further, teachers’ and school-based mental health practitioners’ (SBMHPs) work with shared students has historically tended toward distance rather than collaboration. This article explores the virtual fault line where SBMHPs’ and teachers’ work intersect, concerning student mental health issues. Drawing on qualitative data gathered at three high schools that, to varying degrees, required teachers’ involvement with student mental health issues, this study analyzes the nature of teachers’ work in this area. In particular, the study identifies ways in which teachers provided psychosocial support, as well as how teachers’ and SBMHPs’ work intersected. Findings indicate that uncertainty existed at the three schools about teachers’ involvement with student mental health issues, and that this uncertainty was reinforced by organizational structures that promoted a separation of teaching from SBMH. Implications for practice, professional learning, and research are discussed

Multinma: A comprehensive R package for network meta-analysis of survival outcomes with aggregate data, individual patient data, or a mixture of both

IntroductionSurvival or time-to-event outcomes are commonplace in disease areas such as oncology. Healthcare decision makers require estimates of relative efficacy between different treatment options, however treatments of interest are frequently not all compared in head-to-head randomised controlled trials, and so indirect comparison and network meta-analysis (NMA) methods are required to synthesise evidence from a connected network of trials and treatments. An extension of NMA, multilevel network meta-regression (ML-NMR), is increasingly used to account for differences in effect modifiers between populations where individual patient data are available from one or more trials. However, to date there has been no user-friendly software package that can perform NMA or ML-NMR with survival outcomes; instead analysts have needed to rely on complex bespoke modelling code. MethodsA recent update to the multinma R package provides a user-friendly suite of models and tools for synthesising survival outcomes from multiple trials, with aggregate data, individual patient data, or mixtures of both. Models are fitted in a Bayesian framework using Stan. A full range of parametric proportional hazards and accelerated failure time survival distributions are implemented, along with flexible baseline hazard models via M-splines or piecewise exponential hazards with a novel random walk shrinkage prior that avoids overfitting. Shape parameters may be stratified or regressed on treatment arm and/or covariates to relax proportionality. Right, left, and interval censoring, and delayed entry are all supported.ResultsWe present analyses of two case studies using the multinma package. First, we performed a NMA of published aggregate data from a network of treatments for advanced non-small cell lung cancer using flexible M-spline baseline hazards. We introduced treatment effects onto the spline coefficients to account for non-proportional hazards, and produced estimated survival curves in a target population required for further economic modelling.Second, we performed a ML-NMR using a mixture of individual patient data and aggregate data from a network of treatments for newly-diagnosed multiple myeloma. We adjusted for effect-modifying covariates, and produced population-adjusted estimates for target populations of interest to decision-making. Covariate adjustment removed evidence for non-proportional hazards that was present in unadjusted models.ConclusionsThe multinma package makes NMA and ML-NMR methods accessible to a broad audience. The latest update to include a suite of functionality for survival analysis facilitates application of these methods to widespread settings such as oncology, where until now there was no user-friendly software available

A method for assessing robustness of the results of a star-shaped network meta-analysis under the unidentifiable consistency assumption

Background In a star-shaped network, pairwise comparisons link treatments with a reference treatment (often placebo or standard care), but not with each other. Thus, comparisons between non-reference treatments rely on indirect evidence, and are based on the unidentifiable consistency assumption, limiting the reliability of the results. We suggest a method of performing a sensitivity analysis through data imputation to assess the robustness of results with an unknown degree of inconsistency. Methods The method involves imputation of data for randomized controlled trials comparing non-reference treatments, to produce a complete network. The imputed data simulate a situation that would allow mixed treatment comparison, with a statistically acceptable extent of inconsistency. By comparing the agreement between the results obtained from the original star-shaped network meta-analysis and the results after incorporating the imputed data, the robustness of the results of the original star-shaped network meta-analysis can be quantified and assessed. To illustrate this method, we applied it to two real datasets and some simulated datasets. Results Applying the method to the star-shaped network formed by discarding all comparisons between non-reference treatments from a real complete network, 33% of the results from the analysis incorporating imputed data under acceptable inconsistency indicated that the treatment ranking would be different from the ranking obtained from the star-shaped network. Through a simulation study, we demonstrated the sensitivity of the results after data imputation for a star-shaped network with different levels of within- and between-study variability. An extended usability of the method was also demonstrated by another example where some head-to-head comparisons were incorporated. Conclusions Our method will serve as a practical technique to assess the reliability of results from a star-shaped network meta-analysis under the unverifiable consistency assumption.This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI19C1178). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Methods for Population-Adjusted Indirect Comparisons in Health Technology Appraisal

Standard methods for indirect comparisons and network meta-analysis are based on aggregate data, with the key assumption that there is no difference between the trials in the distribution of effect-modifying variables. Methods which relax this assumption are becoming increasingly common for submissions to reimbursement agencies such as NICE. These use individual patient data from a subset of trials to form population-adjusted indirect comparisons between treatments, in a specific target population. Recently proposed population adjustment methods include the Matching-Adjusted Indirect Comparison (MAIC) and the Simulated Treatment Comparison (STC). Despite increasing popularity, MAIC and STC remain largely untested. Furthermore, there is a lack of clarity about exactly how and when they should be applied in practice, and even whether the results are relevant to the decision problem. There is therefore a real and present risk that the assumptions being made in one submission to a reimbursement agency are fundamentally different to – or even incompatible with – the assumptions being made in another for the same indication. We describe the assumptions required for population-adjusted indirect comparisons, and demonstrate how these may be used to generate comparisons in any given target population. We distinguish between anchored and unanchored comparisons according to whether a common comparator arm is used or not. Unanchored comparisons make much stronger assumptions which are widely regarded as infeasible. We provide recommendations on how and when population adjustment methods should be used, and the supporting analyses that are required, in order to provide statistically valid, clinically meaningful, transparent and consistent results for the purposes of health technology appraisal. Simulation studies are needed to examine the properties of population adjustment methods and their robustness to breakdown of assumptions

Added dietary sulfur and molybdenum has a greater influence on hepatic copper concentration, intake, and performance in Holstein-Friesian dairy cows offered a grass silage- rather than corn silage-based diet

To test the hypothesis that the metabolism of Cu in dairy cows is affected by basal forage and added S and Mo, 56 dairy cows that were 35 (standard error ± 2.2) days postcalving and yielding 38.9 kg of milk/d (standard error ± 0.91) were offered 1 of 4 diets in a 2 × 2 factorial design for a 14-wk period. The 4 diets contained approximately 20 mg of Cu/kg of dry matter (DM), and had a corn silage-to-grass silage ratio of 0.75:0.25 (C) or 0.25:0.75 (G) and were either unsupplemented (−) or supplemented (+) with an additional 2 g of S/kg of DM and 6.5 mg of Mo/kg of DM. We found an interaction between forage source and added S and Mo on DM intake, with cows offered G+ having a 2.1 kg of DM lower intake than those offered G−, but no effect on the corn silage-based diets. Mean milk yield was 38.9 kg/d and we observed an interaction between basal forage and added S and Mo, with yield being decreased in cows offered G+ but increased on C+. No effect of dietary treatment on milk composition or live weight was noted, but body condition was lower in cows fed added S and Mo irrespective of forage source. We found an interaction between forage source and added S and Mo on milk somatic cell count, which was higher in cows offered G+ compared with G−, but not in cows fed the corn silage-based diets, although all values were low (mean values of 1.72, 1.50, 1.39, and 1.67 log10/mL for C−, C+, G−, and G+, respectively). Mean plasma Cu, Fe, and Mn concentrations were 13.8, 41.3, and 0.25 µmol/L, respectively, and were not affected by dietary treatment, whereas plasma Mo was 0.2 µmol/L higher in cows receiving added S and Mo. The addition of dietary S and Mo decreased liver Cu balance over the study period in cows fed either basal forage, but the decrease was considerably greater in cows receiving the grass silage-based diet. Similarly, hepatic Fe decreased more in cows receiving G than C when S and Mo were included in the diet. We concluded that added S and Mo reduces hepatic Cu reserves irrespective of basal forage source, but this decrease is considerably more pronounced in cows receiving grass silage- than corn silage-based rations and is associated with a decrease in intake and milk performance and an increase in milk somatic cell count

Calibrating a network meta-analysis of diabetes trials of sodium glucose co-transporter 2 inhibitors, glucagon-like peptide-1 receptor analogues and dipeptidyl peptidase-4 inhibitors to a representative routine population : a systematic review protocol

Introduction: Participants in randomised controlled trials (trials) are generally younger and healthier than many individuals encountered in clinical practice. Consequently, the applicability of trial findings is often uncertain. To address this, results from trials can be calibrated to more representative data sources. In a network meta-analysis, using a novel approach which allows the inclusion of trials whether or not individual-level participant data (IPD) is available, we will calibrate trials for three drug classes (sodium glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP1) receptor analogues and dipeptidyl peptidase-4 (DPP4) inhibitors) to the Scottish diabetes register. Methods and analysis: Medline and EMBASE databases, the US clinical trials registry (clinicaltrials.gov) and the Chinese Clinical Trial Registry (chictr.org.cn) will be searched from 1 January 2002. Two independent reviewers will apply eligibility criteria to identify trials for inclusion. Included trials will be phase 3 or 4 trials of SGLT2 inhibitors, GLP1 receptor analogues or DPP4 inhibitors, with placebo or active comparators, in participants with type 2 diabetes, with at least one of glycaemic control, change in body weight or major adverse cardiovascular event as outcomes. Unregistered trials will be excluded. We have identified a target population from the population-based Scottish diabetes register. The chosen cohort comprises people in Scotland with type 2 diabetes who either (1) require further treatment due to poor glycaemic control where any of the three drug classes may be suitable, or (2) who have adequate glycaemic control but are already on one of the three drug classes of interest or insulin. Ethics and dissemination: Ethical approval for IPD use was obtained from the University of Glasgow MVLS College Ethics Committee (Project: 200160070). The Scottish diabetes register has approval from the Scottish A Research Ethics Committee (11/AL/0225) and operates with Public Benefit and Privacy Panel for Health and Social Care approval (1617-0147). PROSPERO registration number: CRD42020184174

Levels of selected minerals, nitric oxide, and vitamins in aborted Sakis sheep raised under semitropical conditions

The serum levels of calcium, phosphorus, magnesium, copper, zinc and iron and of nitric oxide, retinol, and β-carotene were determined in Sakiz ewes that had experienced an abortion and in healthy controls. Ten healthy and 25 aborted Sakiz sheep were selected from Afyon zone in western Turkey. Their ages ranged between 2 and 4 years weighing between 40 and 60 kg at the time of experiment. All of the abortions occurred in October. The concentrations of retinol, β-carotene, phosphorus, and zinc were significantly lower and those of calcium and nitric oxide were increased in aborted ewes relative to healthy controls. The serum levels of iron, copper, and magnesium were not significantly different among the two groups. In conclusion, abortion is an important problem in commercially important species of ruminants in many regions in the tropics including of western Turkey. Deficiencies of retinol, β-carotene, phosphorus and zinc, and the increase of calcium and nitric oxide concentration may play an important role in the etiology of abortion in ewes. Prophylactic measures such as vitamin and mineral supplementation may be of help to prevent or reduce the incidence of abortion in sheep